Evidence map›Paper›PMID 34450775›Full record

ArticleSensors (Basel, Switzerland)2021

A Flexible Baseline Measuring System Based on Optics for Airborne DPOS.

Yanhong Liu, Wen Ye, Bo Wang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yanhong LiuResearch Institute for Frontier Science, Beihang University, Beijing 100191, China.ORCID 0000-0001-8291-6423
Wen YeDivision of Mechanics and Acoustic Metrology, National Institute of Metrology, Beijing 100029, China.ORCID 0000-0001-9769-9863
Bo WangResearch Institute for Frontier Science, Beihang University, Beijing 100191, China.ORCID 0000-0002-2888-0279

Funding

Basic research of National Institute of Metrology AKYJJ1906the National Natural Science Foundation of China 61703021the National Natural Science Foundation of China 61721091the National Natural Science Foundation of China 61722103the National Natural Science Foundation of China 61763005the National Natural Science Foundation of China 61873019the National Natural Science Foundation of China 61901431the National Natural Science Foundation of China 61973020the National Natural Science Foundation of China U1804161
6 · The paper itself

Abstract

Three-dimensional imaging for multi-node interferometric synthetic aperture radar (InSAR) or multi-task imaging sensors has become the prevailing trend in the field of aerial remote sensing, which requires multi-node motion information to carry out the motion compensation. A distributed position and orientation system (DPOS) can provide multi-node motion information for InSAR by transfer alignment technology. However, due to wing deformation, the relative spatial relationship between the nodes will change, which will lead to lower accuracy of the transfer alignment. As a result, the flexible baseline between the nodes affects the interferometric phase error compensation and further deteriorates the imaging quality. This paper proposes a flexible baseline measuring system based on optics, which achieves non-connect measurement and overcomes the problem that it is difficult to build an accurate wing deformation model. An accuracy test was conducted in the laboratory, and results showed that the measurement accuracy of the baseline under static and dynamic conditions was less than 0.3 mm and 0.67 mm, respectively.

Indexed as

aerial remote sensingdistributed position and orientation systemflexible baseline measurement

Identifiers

PMID34450775
PMCPMC8398224

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.